The __________ feature of AWS Lambda allows you to reuse common code across multiple functions, reducing duplication in deployment packages.
- Lambda Events
- Lambda Functions
- Lambda Layers
- Lambda Triggers
Lambda Layers enable you to centrally manage common code or dependencies across multiple Lambda functions, reducing the size of deployment packages and minimizing duplication.
In AWS Lambda, you can leverage __________ to create layers containing shared libraries, custom runtimes, or other dependencies.
- AWS CLI (Command Line Interface)
- AWS Lambda Console
- AWS SAM (Serverless Application Model)
- AWS SDK (Software Development Kit)
AWS SAM (Serverless Application Model)
Scenario: You're tasked with optimizing the performance of an existing Lambda function that interacts with a DynamoDB table. What strategies would you employ to improve its efficiency?
- Batch multiple DynamoDB operations
- Enable DynamoDB Accelerator (DAX)
- Implement DynamoDB Streams
- Increase the provisioned concurrency
DynamoDB Accelerator (DAX) is an in-memory caching service that can significantly improve the read performance of DynamoDB tables accessed by Lambda functions.
What is a deployment package in AWS Lambda?
- A relational database
- A virtual machine instance
- A zip archive containing your function code and any dependencies
- An email server
A deployment package in AWS Lambda is typically a zip archive that includes your function code along with any dependencies required for execution.
How does AWS Lambda handle deployment of functions?
- Automatically upon function creation or update
- By scheduling deployments at specific times
- Manually by the user
- Through third-party tools only
AWS Lambda automatically handles the deployment of functions whenever they are created or updated, ensuring the latest code is available for execution.
How can you optimize the size of a deployment package for an AWS Lambda function?
- Enable verbose logging, Include comprehensive documentation, Add encryption keys
- Increase dependencies, Use a larger runtime, Include all available libraries
- Minimize dependencies, Use a smaller runtime, Remove unused code and libraries
- Minimize memory allocation, Include large data files, Add debugging information
To optimize the size of a deployment package for an AWS Lambda function, minimize dependencies, use a smaller runtime, and remove unused code and libraries.
What is the role of AWS SAM (Serverless Application Model) in managing deployment packages?
- AWS SAM automates manual deployment processes
- AWS SAM increases the complexity of managing serverless applications
- AWS SAM replaces AWS Lambda in managing serverless applications
- AWS SAM simplifies defining and deploying serverless applications
The role of AWS SAM (Serverless Application Model) in managing deployment packages is to simplify defining and deploying serverless applications by providing a declarative way to define resources and configurations.
How does AWS Lambda handle updates to deployment packages?
- Immutable updates
- In-place updates
- Manual updates
- Versioned updates
AWS Lambda supports in-place updates, where the new deployment package replaces the previous one without creating a new version or alias.
What are the considerations for managing versioning of deployment packages in AWS Lambda?
- Cost optimization
- Dependency management
- Rollback strategy
- Security measures
Versioning deployment packages in AWS Lambda requires considering dependencies to ensure compatibility and consistency across versions.
To include external dependencies in an AWS Lambda deployment package, you can use __________ or package managers like npm for Node.js functions.
- build automation tools
- dependency injection
- virtual environments
- zip archives
Zip archives are commonly used to package AWS Lambda deployment packages, allowing you to include external dependencies.